Intuitivno pretraživanje baze slike kao potpora označavanju slika

Image annotation is typically performed manually since automatic image annotation approaches have not matured yet to be used in practice. Consequently, image annotation is a labour intensive and time consuming task. In this paper, we show how an image browsing system can be employed to support efficient and effective (manual) annotation of image databases. In contrast to other approaches, which typically present images in a linear fashion, we employ a visualisation where images are arranged by mutual visual similarity. Since in this arrangement similar images are close to each other, they can easily be selected and annotated together. Organisation on a grid layout prevents image overlap and thus contributes to a clear presentation. Large image databases are handled through a hierarchical data structure where each image in the visualisation can correspond to a cluster of images that can be expanded by the user. Experimental results indicate that annotation can be performed faster on our proposed system.Označavanje slika obično se obavlja ručno jer automatski pristupi još nisu dovoljno kvalitetni kako bi se koristili u praksi. Zbog toga je označavanje slika u bazi vremenski zahtjevno. U ovom radu pokazat ćemo kako se sustav za pregled slika u bazi može koristiti kao učinkovita potpora ručnom označavanju slika. Za razliku od drugih pristupa, koji prikazuju slike u linearnom poretku, korištena je vizualizacija u kojoj su slike složene po međusobnoj sličnosti. Budući da su na taj način slične slike međusobno blizu jedna drugoj, lako ih je selektirati i zajednički označiti. Slike su organizirane u mrežni prikaz radi sprječavanja preklapanja i jasnije prezentacije. Velike baze podataka organizirane su u hijerarhijsku strukturu gdje svaka slika u pojedinoj vizualizaciji može pripadati skupu slika čiji prikaz korisnik po želji može proširivati. Rezultati provedenih eksperimenata pokazuju da se označavanje slika pomoću predloženog sustava može obavljati brže nego na uobičajeni način

Collaborative yet independent: Information practices in the physical sciences

In many ways, the physical sciences are at the forefront of using digital tools and methods to work with information and data. However, the fields and disciplines that make up the physical sciences are by no means uniform, and physical scientists find, use, and disseminate information in a variety of ways. This report examines information practices in the physical sciences across seven cases, and demonstrates the richly varied ways in which physical scientists work, collaborate, and share information and data. This report details seven case studies in the physical sciences. For each case, qualitative interviews and focus groups were used to understand the domain. Quantitative data gathered from a survey of participants highlights different information strategies employed across the cases, and identifies important software used for research. Finally, conclusions from across the cases are drawn, and recommendations are made. This report is the third in a series commissioned by the Research Information Network (RIN), each looking at information practices in a specific domain (life sciences, humanities, and physical sciences). The aim is to understand how researchers within a range of disciplines find and use information, and in particular how that has changed with the introduction of new technologies

Connecting the dots : playful interaction with scientific image data in repositories

Scientific practice is an activity that is data-intensive and widely supported by computerized systems, data repositories included. It is also an activity that is highly creative and, as such, can benefit from a moment of openness, playfulness and exploration. Motivated also by recent developments in the field of Human Computer Interaction regarding play and games, this work investigates playfulness as a desirable attribute of a scientist's interaction with scientific data in repositories. Focus is on data repositories of a specific domain of science, i.e. the life sciences, and of a particular type of data, i.e. image data. Having introduced a new but relevant attribute for interfaces to scientific image repositories, i.e. playfulness, the question we ask is the following: What could playfulness with scientific images amount to and how do we design for it? Via case studies and reviews, we flesh out particular elements of play for exploration and implement artefacts, i.e. interfaces and games, that exemplify instances of playful interaction with image research material in collections.LEI Universiteit LeidenComputer Systems, Imagery and Medi

Attitudes to the rights and rewards for author contributions to repositories for teaching and learning

In the United Kingdom over the past few years there has been a dramatic growth of national and regional repositories to collect and disseminate resources related to teaching and learning. Most notable of these are the Joint Information Systems Committee’s Online Repository for [Learning and Teaching] Materials as well as the Higher Education Academy’s subject specific resource databases. Repositories in general can hold a range of materials not only related to teaching and learning, but more recently the term ‘institutional repository’ is being used to describe a repository that has been established to support open access to a university’s research output. This paper reports on a survey conducted to gather the views of academics, support staff and managers on their past experiences and future expectations of the use of repositories for teaching and learning. The survey explored the rights and rewards associated with the deposit of materials into such repositories. The findings suggest what could be considered to be an ‘ideal’ repository from the contributors’ perspective and also outlines many of the concerns expressed by respondents in the survey

Image mining: trends and developments

[Abstract]: Advances in image acquisition and storage technology have led to tremendous growth in very large and detailed image databases. These images, if analyzed, can reveal useful information to the human users. Image mining deals with the extraction of implicit knowledge, image data relationship, or other patterns not explicitly stored in the images. Image mining is more than just an extension of data mining to image domain. It is an interdisciplinary endeavor that draws upon expertise in computer vision, image processing, image retrieval, data mining, machine learning, database, and artificial intelligence. In this paper, we will examine the research issues in image mining, current developments in image mining, particularly, image mining frameworks, state-of-the-art techniques and systems. We will also identify some future research directions for image mining

The Graphic Design Archive: Generating Higher Levels of Scholarship Through a User Experience Approach to Scholarly Image Database Design

Innovations in the user experiences of digital image collections have taken image-based searching from the realm of basic one-way searches and sorts and delivered users a new world of dynamic and interactive explorations that offer mechanisms for higher-level cognitive functions such as comparing, analyzing, sorting, sharing, designing, and creating in an intuitive environment. While innovations in image search functionality often occur first in non-academic applications (e.g., social media), image archives meant to amasse and preserve visual information for the ages would benefit by adopting and adapting search innovations. Students and scholars that access image-based archives of information to gather resources and conduct research employ high-level thinking during the user experience of the digital archive. By using Bloom’s Taxonomy to categorize levels of user cognition during a search, user experience functions will be assessed and new functions will be developed and implemented to give users of the Graphic Design Archive a level of search functionality and flexibility that meets the demands of scholarly research. The methods used will include conversational interface design and they will be applied to both a desktop and web application. Generating higher levels of scholarship through the use of this new, adaptable interface is the intended outcome

Digital Image Access & Retrieval

The 33th Annual Clinic on Library Applications of Data Processing, held at the University of Illinois at Urbana-Champaign in March of 1996, addressed the theme of "Digital Image Access & Retrieval." The papers from this conference cover a wide range of topics concerning digital imaging technology for visual resource collections. Papers covered three general areas: (1) systems, planning, and implementation; (2) automatic and semi-automatic indexing; and (3) preservation with the bulk of the conference focusing on indexing and retrieval.published or submitted for publicatio

Browse-to-search

This demonstration presents a novel interactive online shopping application based on visual search technologies. When users want to buy something on a shopping site, they usually have the requirement of looking for related information from other web sites. Therefore users need to switch between the web page being browsed and other websites that provide search results. The proposed application enables users to naturally search products of interest when they browse a web page, and make their even causal purchase intent easily satisfied. The interactive shopping experience is characterized by: 1) in session - it allows users to specify the purchase intent in the browsing session, instead of leaving the current page and navigating to other websites; 2) in context - -the browsed web page provides implicit context information which helps infer user purchase preferences; 3) in focus - users easily specify their search interest using gesture on touch devices and do not need to formulate queries in search box; 4) natural-gesture inputs and visual-based search provides users a natural shopping experience. The system is evaluated against a data set consisting of several millions commercial product images. © 2012 Authors